Marine Pollution Bulletin 163 (2021) 111969

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Marine Pollution Bulletin

journal homepage: www.elsevier.com/locate/marpolbul

Assessment of potential ecological risk of microplastics in the coastal

sediments of India: A meta-analysis
M. Ranjani a, S. Veerasingam b, *, R. Venkatachalapathy a, M. Mugilarasan c, Andrei Bagaev d,
Vladimir Mukhanov e, P. Vethamony b
a
Department of Physics, Annamalai University, Annamalai Nagar 608 002, Tamil Nadu, India
b
Environmental Science Center, Qatar University, P.O. Box: 2713, Qatar
c
National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
d
Department of Shelf Hydrophysics, Federal Research Center Marine Hydrophysical Institute of RAS, Sevastopol 299011, Russia
e
A.O. Kovalevsky Institute of Biology of the Southern Seas of RAS, Sevastopol, Russia

A R T I C L E I N F O A B S T R A C T

Keywords: Abundance, chemical composition and ecological risk of microplastics (MPs) in terrestrial and marine envi­
Microplastics ronments have merited substantial attention from the research communities. This is the first attempt to
Sediments comprehend the ecological risk of MPs in sediments along the Indian coast using meta-data. Polymer hazard
Polymer hazard index
index (PHI), pollution load index (PLI) and potential ecological risk index (PERI) were used to evaluate the
Pollution load index
Potential ecological risk index
quality of sediments. Areas have high PHI values (>1000) due to the presence of polymers with high hazard
Coast of India scores such as polyamide (PA) and polystyrene (PS). According to PLI values, sediments along the west coast of
India (WCI) are moderately contaminated with MPs (PLI: 3.03 to 15.5), whereas sediments along the east coast of
India (ECI) are less contaminated (PLI: 1 to 6.14). The PERI values of sediments along the Indian coast showed
higher ecological risk for the metropolitan cities, river mouths, potential fishing zones and the remote islands.

1. Introduction Though large plastic debris present a visible environmental risk

(Provencher et al., 2017), there is an increasing awareness and concern
Accumulation of plastic debris in the terrestrial and marine about the environmental and eco-toxicological impacts of tiny pieces of
ecosystem from the poles to the deep ocean to the coast is found ubiq­ plastic debris (1 μm–5 mm) called ‘microplastic’ (MP) (Hartmann et al.,
uitously (Obbard et al., 2014; Veerasingam et al., 2020a; Cunningham 2019), originating from a variety of sources with different chemical
et al., 2020). Meanwhile, petrochemical manufacturing industry has properties. MP is found in different environmental matrices, including
declared over 204 billion U.S. dollar investment to the shale gas boom, sediments (Veerasingam et al., 2016a, 2016b), water (Cozar et al.,
leading to a projected acceleration in virgin plastic production (ACC, 2017), biota (Redondo-Hasselerharm et al., 2020), salt (Kim et al., 2018)
2020). Borrelle et al. (2020) evaluated influence of three comprehensive and air/dust (Brahney et al., 2020) all over the world. It is estimated that
management strategies - plastic waste reduction, waste management, ~8 million tons of MP (Jambeck et al., 2015) and 1.5 million tons of
and environmental recovery - at diverse levels of effort to assess plastic primary MP (Boucher and Friot, 2017) enter the ocean annually.
emissions in 2030 for 173 countries. About 19 to 23 million metric tons Ingestion of MPs has been found in more than 2000 aquatic species
of plastic waste, generated globally, entered into the aquatic ecosystems. worldwide, ranging from zooplankton to baleen whales (Savoca et al.,
Borrelle et al. (2020) found that the predicted growth in plastic waste 2016; Lamb et al., 2018; Zhu et al., 2019). Therefore, the resolutions of
exceeds efforts to mitigate plastic pollution around the world. Even with United Nations Environment Assembly on Marine litter and Micro­
immediate and concerted action, 710 million tons of plastic waste plastics (UNEA, 2019) and Goal 14.1 of the United Nations Sustainable
cumulatively entered the aquatic and terrestrial ecosystems. Therefore, Development Goals (UN-SDG, 2018) stressed the need to reduce plastic
many countries around the world are struggling to manage the current emission into the environment.
volume of plastic waste and plastic contamination in the environment MPs are usually referred to as a ‘cocktail of contaminants’ due to
(UNEA, 2019; Lau et al., 2020). their association with additives (added or produced during

* Corresponding author.
E-mail address: v.subramanian@qu.edu.qa (S. Veerasingam).

https://doi.org/10.1016/j.marpolbul.2021.111969
Received 17 November 2020; Received in revised form 4 January 2021; Accepted 6 January 2021
Available online 27 January 2021
0025-326X/© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

manufacturing), heavy metals, and persistent organic pollutants present conducted a meta-analysis of published work, and evaluated potential
in the environment (Rochman, 2015). This mixture of contaminants can ecological risk of MPs in the terrestrial and marine sediments of India.
be bioavailable to various biota, including human upon ingestion The main objectives are (i) extracting data on concentration and poly­
(Hartmann et al., 2017). Therefore, it is of utmost importance to put mer composition of MPs in sediments from the literature, (ii) identifying
efforts toward an eco-toxicological risk assessment of MPs to obtain a the potential sources of MPs and their controlling factors, (iii) assessing
clear idea of the potential threat when they are ingested by biota. In the degree of MP contamination using polymer hazard index, pollution
India, in the past few decades due to rapid industrialization, economic load index and potential ecological risk and (iv) providing recommen­
development and climatic change, pollutants (organic and inorganic) dations on the importance of ecological risk assessment of microplastic
have contaminated estuarine sediments via several pathways and pollution.
resulted in associated coastal and marine environmental health prob­
lems (Chakraborty et al., 2014). For the past three years, the abundance 2. Materials and methods
and polymer composition of MPs in different environmental matrices in
India have been studied extensively (Veerasingam et al., 2020b). How­ 2.1. Study area
ever, ecological risk assessment of MPs in sediments, based on the
observed results, has not received much attention. In this study, we India has a coastline of ~7500 km, excluding its island territories and

Fig. 1. The locations of sediment samples collected by the researchers for their works from the Indian coast. The geographical co-ordinates of sampling locations are
extracted from the literature.

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M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

an exclusive economic zone (EEZ) of 2 million km2. The climate of In­ polymer hazard assessment of MPs was calculated using the following
dian sub-continent is dominated by monsoon systems. There are 11 formula:
major rivers (Ganga, Brahmaputra, Indus, Krishna, Godavari, Mahanadi, ∑
Cauvery, Palar, Pennar, Narmada, and Tapti), 47 medium rivers and 162 PHI = Pn × S n
small rivers in India, having a mean annual run-off of 1645 km3,
although not all these rivers discharge into the sea (Sarkar et al., 2008). where, ‘PHI’ is the calculated polymer hazard index caused by MP, ‘Pn’ is
India has 28 states and 8 Union Territories with the total population the percent of specific polymer types (Table 1) collected at each sam­
of 1353 million. Among these states, 9 are coastal states (Gujarat, pling location, and ‘Sn’ is the hazard scores of polymer types of MPs
Maharashtra, Goa, Karnataka, Kerala, Tamil Nadu, Andhra Pradesh, derived from Lithner et al. (2011).
Odisha, and West Bengal) and among the Territories, 4 are coastal Union
Territories (Andaman and Nicobar Islands, Dadra and Nagar Haveli and 2.4. Pollution load index (PLI)
Daman and Diu, Lakshadweep Islands and Puducherry) (Fig. 1). The
coastline is rich in diverse ecosystems, including estuaries, lagoons To assess the degree of MP pollution in surface sediments from the
mangroves, seagrasses, coral reefs, mudflats, and salt marshes. The estuarine, coastal and marine environment in India, an integrated
coastal zone of India consists of widespread fertile delta plains, tourism pollution load index (PLI) was calculated based on Tomlinson et al.
related activities, industries, harbors, and land ports. In India, the (1980). PLI at each location is related to MP concentration factors (CFi)
annual plastic consumption is nearly 5.6 million tons (Naidu et al., as given below:
2018). Plastic litter related to fishing industry on the beaches is more
Ci
prevalent along the Indian coast (Kaladharan et al., 2020). The dy­ CF i =
Coi
namics of the Indian Ocean is controlled by the southwest (SW: June –
September) and northeast (NE: November – February) monsoons. Due to √̅̅̅̅̅̅̅̅
PLI = CF i
run-off during SW and NE monsoons, large quantity of plastic waste
enters into the Indian ocean through several perennial rivers along the CFi of the MP is the quotient of the MP concentration at each location
Indian Ocean (Lebreton et al., 2017; van der Mheen et al., 2020). (Ci) and the background MP concentration (Coi). The lowest concen­
tration of MP value detected in the sediment sample was considered as a
background value.
2.2. Data collection, extraction and quality assessment

In order to extract concentration and polymer composition of MP 2.5. Potential ecological risk index (PERI)
data from the published literature, systematic literature search was
conducted using the Web of Knowledge (all databases) with the key­ Potential ecological risk index (PERI) is also used to assess the degree
words: “Sediment”, “microplastic”, “plastic debris” and “marine debris”, of contamination of MPs in the sediments (Peng et al., 2018). The
“Arabian Sea”, “Bay of Bengal”, “India”, and “Indian Ocean” from the equations used to calculate the PERI are as follows:
year 2006 to October 2020. Review articles and book chapters were /
excluded. Our search resulted in a collection of literature spanning in the Cfi = Ci Cni
fields of environmental pollution, oceanography, marine biology, toxi­
cology, and ecology. All the secondary data available in the peer- ∑n
Pn
Tri = × Sn
reviewed research articles focusing on different aspects of microplastic n=1
Ci
pollution in the surface sediments in the coastal regions of India were
included in the analysis. For each study, we recorded information Eri = Tri × Cfi
regarding polymer types of MPs and their identification techniques.
Detailed sampling and analytical methods used for the study of MPs in where, Ci and Cin are the concentration of pollutant ‘i’ (i.e., microplastic)
different environmental matrices in India are explained by Veerasingam and unpolluted samples, respectively. The toxicity coefficient (Tir) rep­
et al. (2020b). Fig. S1 summarizes the data collection and extraction resents toxicity level and biological sensitivity. The toxicity coefficient is
process. the sum of the percentage of certain polymers in the total sample (Pn/Ci)
multiplied by the hazard score of plastic polymers (Sn).
2.3. Polymer hazard index (PHI)
2.6. Hydrodynamics
To evaluate the potential risks of MPs in surface sediments, we have
considered both the concentration and the chemical composition of MPs Scatterometers are able to measure ocean surface wind vectors in
(Xu et al., 2018). The chemical toxicity of different polymer types of MPs both clear and cloudy conditions. Therefore, in this study, wind data
is considered to evaluate its ecological harm (Lithner et al., 2011). The during the southwest (SW) and northeast (NE) monsoons of 2019 from

Table 1
Detailed information for the primary hazard statements and scores of MP polymers found in sediments from the Indian coast.
Polymer Monomer Density (g cm− 3) Primary hazard statements Hazard level Score

Polyethylene (PE) Ethylene 0.91–0.97 Extremely flammable gas 1 11

May cause drowsiness or dizziness 2
Polypropylene (PP) Propylene 0.89–0.92 Extremely flammable gas 1 1
Polystyrene (PS) Styrene 0.28–1.04 Flammable liquid and vapour 0 30
Harmful if inhaled 2
Polyethylene terephthalate (PET) Ethanediol 1.37–1.38 Harmful if swallowed 2 4
Polyamide (PA) Hexamethylenediamine 1.14–1.15 Harmful in contact with skin 2 47
Harmful if swallowed 2
May cause respiratory irritation 2
Causes severe skin burns and eye damage 3

(Data source: Lithner et al. (2011).)

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M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

the advanced Scatterometer (ASCAT) onboard the meteorological Ramasamy, 2017), we can find high concentration of MPs. The abun­
operational platform (MetOp-B) satellite (http://apdrc.soest.hawaii. dance of MPs is also found in the UNESCO Biosphere reserve (Gulf of
edu/las/v6/dataset?catitem=12790) was used. The ASCAT sea surface Mannar). The lowest MP concentration is found in the Gulf of Mannar
wind product is a one-day composite product with a spatial resolution of (12.22 items/kg) (Patterson et al., 2019) and Idinthakarai (2.2 items/
0.25◦ × 0.25◦ . The surface current patterns in the northern Indian Ocean m2) (Karthik et al., 2018). Based on global modelling, Eriksen et al.
during SW and NE monsoon of 2019 were obtained from the Ocean (2014) estimated that there was approximately 59,130 tons of plastics in
Surface Current Analysis Real-time (OSCAR) data (www.oscar.noaa. the surface waters across the Indian Ocean. Jambeck et al. (2015) esti­
gov). OSCAR is an ocean-surface current data product, which is mated that about 4.49 million tons/year plastic waste was generated in
computed from satellite-derived measurements of sea level anomaly 2010 from India, in which 85% of the waste was inadequately managed.
(SLA), sea surface wind (SSW), and sea surface temperature (SST). The Lebreton et al. (2017) showed that the River Ganges is the second largest
data are available at 5-day intervals and at 1◦ × 1◦ spatial resolution contributor (115,000 tons) of plastic to the ocean. Though these model
(Veerasingam et al., 2016a). estimates were not validated due to inadequate monitoring data, the
available field measurements and modelling studies do revealed that
3. Results and discussion most of the terrestrial and marine sediments in India are contaminated
with MPs. However, baseline level of MPs in most of the terrestrial re­
3.1. Abundance and polymer composition of MPs in the coastal and gions, central and northeast coastal regions, nearshore and offshore
marine sediments regions have not yet been established. Therefore, in order to fill the
knowledge gap in the distribution of MPs in terrestrial and marine sys­
The concentration of MPs in the terrestrial and marine sediments of tems of India, more studies are needed.
India is illustrated in Figs. 2a and 3a. The literature data shows that MP We have calculated the average percentage of polymer types of MPs
contamination is widespread in both terrestrial and marine environ­ found in the terrestrial and marine sediments (Figs. 2b and 3b) from the
ments. In most of the research papers, the concentrations of MPs in percentage value of polymer composition reported in the literature.
sediments are reported as ‘MP items/kg’ and ‘MP items/m2’. A few Among the reviewed studies, the frequently identified polymer types of
studies reported it in percentage and also provided the total number of MPs in sediments include high-density/low-density polyethylene (HD/
MP items. The ranges of average MP concentration in sediments along LD-PE), polypropylene (PP), polystyrene (PS), polyethylene tere­
the Indian coast varied between 12.22 items/kg and 439 items/kg phthalate (PET) and polyamide (PA). Overall, PE (47.7%) and PP
(Fig. 2a) and between 2.2 items/m2 and 526.5 items/m2 (Fig. 3a). The (18.8%) were the most abundant polymer types found in the sediment
highest concentration of MPs was found in the metropolitan cities samples. As per 2019 global plastic production data, PE (29.7%) and PP
(Mumbai along the WCI (Maharana et al., 2019), and Chennai along the (19.3%) were the major composition of plastic material produced as
ECI (Sathish et al., 2019)), and in the River Ganges (Sarkar et al., 2019). short life-cycle products (Plastic Europe, 2019; Geyer et al., 2017).
The remote islands (Andaman and Nicobar) situated in the East Indian Therefore, the predominance of PE, PP and PET type of polymers might
Ocean is also highly contaminated by MPs (Goswami et al., 2020). Even have been originated from the higher production rate and are widely
in the terrestrial freshwater lakes such as Veeranam Lake (ECI) (Man­ used in food packaging, agricultural film, plastic bags and plastic bottles.
ikanda Bharath et al., 2021) and Vembanad Lake (WCI) (Sruthy and The presence of PA type MPs in the northern Indian Ocean (Andaman

Fig. 2. (a) Average concentration of MPs (items/kg) and (b) their corresponding polymer composition in terrestrial and marine sediments in India. Data were
extracted from Amrutha and Warrier (2020), Goswami et al. (2020), Kalpana et al. (2020), Manikanda Bharath et al. (2021), Patterson et al. (2019), Patterson et al.
(2020), Sarkar et al. (2019), Sathish et al. (2019) and Tiwari et al. (2019).

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M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

Fig. 3. (a) Average concentration of MPs (items/m2) and (b) their corresponding polymer composition in terrestrial and marine sediments in India. Data were
extracted from Jeyasanta et al. (2020), Karthik et al. (2018), Maharana et al. (2019), Robin et al. (2020) and Sruthy and Ramasamy (2017).

and Nicobar Islands) were much higher than those found along the ECI of the plastic debris entered into the Indian Ocean are from sea-based
and WCI. sources (Veerasingam et al., 2017). MP polymers (i.e., abundance of
PA) and shapes found along the southeast coast of India revealed that
3.2. Potential sources of MPs the sea-originated plastic debris from aquaculture and fisheries have
become significant sources of MPs. Automatic Identification System
MPs in the marine sediments along the Indian coast are originated (AIS) provided annually averaged traffic density map (Fig. S3), and that
from both land- and sea-based sources (Veerasingam et al., 2016a, shows that congested shipping lanes are lower in the Bay of Bengal (ECI)
2016b). The abundance and polymer types of MPs along the Indian coast than the Arabian Sea (WCI). The southern tip of India is situated very
demonstrate a close association with inland sources such as urbaniza­ close to the International shipping routes. Moreover, Fig. S3 confirms
tion, industrialization and sea-based sources such as fishing and ship­ that widespread fishing vessel activities are going on off ECI and WCI.
ping activities. Lebreton et al. (2012) found that 80% of plastic debris Therefore, abundance of PA composition of MPs might have been
derived from the land-based sources (especially through coastal popu­ derived from the unintentional and/or intentional discard of fishing nets
lation and rivers) ended into the ocean. Fig. S2 shows that the popula­ and related debris. Recently, Kaladharan et al. (2020) confirmed that
tion density along the WCI is relatively higher than those found along there is growing harmful effects of plastic waste in the potential fishing
the ECI. It is reported that the population of India has doubled during areas along the Indian coastal region. Moreover, cargo lost from mer­
1975–2010 and the amount of municipal solid waste (MSW) has tripled chant ships, and trash thrown overboard may also lead to an important
(Singh et al., 2011). Based on the Central Pollution Control Board report input of plastics into the sea, particularly in the Strait of Malacca (Duis
(CPCB, 2018), in India, 62 MT of solid waste was generated in 2015, out and Coors, 2016; Li et al., 2021). Airborne transport of MPs is also
of which 82% was collected (in this 28% was treated, and the remaining another important pathway for the plastics to move from land to ocean.
was dumped in the open) and 18% was treated as litter. It is estimated Recently, Wang et al. (2020) found that MP in the atmosphere over the
that about 300 million tons per year of MSW will be generated by 2051 East Indian Ocean might have been originated from the MP emissions
due to increase in the population (≈1823 million), if urban local bodies from the adjacent continent.
(ULBs) in India continue to rely on landfill route for MSW management
(Joshi and Ahmed, 2016). Open dumping causes surface water pollution 3.3. Factors influencing the distribution and transportation of MPs
due to material uncontrolled flows and leachate mismanagement.
Therefore, urbanized and densely populated coastal areas around the PE and PP are produced in large quantities globally and widely used.
Indian Ocean could be the major potential source of MPs (Li et al., MPs derived from both land and sea-based sources are transported
2021), which is in consistent with the modelling results obtained by mainly by winds and currents in the ocean (Law et al., 2010; Kane et al.,
Jambeck et al. (2015). However, we find that average annual discharges 2020). The low specific densities of PE and PP allow them to float on
into the Indian Ocean from the rivers along the ECI are higher than that water surface and travel long distances through ocean currents and
along the WCI (Table S1). The abundance and polymer composition of winds, resulting in wide distribution, even in remote islands both un­
MPs along the Indian coast showed the highest polymer diversity pattern inhabited (Tinnakara Island, Lakshadweep) and inhabited (Andaman
in metropolitan cities and river mouths along the Indian coast. This and Nicobar Islands). Fig. 4 shows the circulation in the northern Indian
proves that the regional man-made activities influence the pollution Ocean, influenced by both SW and NE monsoon winds (Schott et al.,
characteristics of MPs in the nearshore marine environment. Nearly 20% 2009). In summer, the clockwise ocean circulation is dominated by the

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M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

Fig. 4. The wind and current patterns during the southwest and northeast monsoon seasons in the north Indian Ocean.

SW monsoon, whereas the anticlockwise ocean circulation is formed 3.4. Risk assessment of MPs in sediments
under the influence of NE monsoon. The East Indian Coastal Current
(EICC) and West Indian Coastal Current (WICC) play the important role MPs are ingested by many terrestrial and marine organisms, such as
on the transportation of floating debris between the Bay of Bengal and mollusc (Naidu, 2019), fish (Kumar et al., 2018), shrimp (Daniel et al.,
the Arabian Sea (Veerasingam et al., 2017). Dharani et al. (2003) found 2020) and crab (Piarulli et al., 2019), which may transfer up to human
that the garbage generated in the coastal areas of Malaysia, Singapore, via food chains. Therefore, it would pose significant risks to the biota as
Sumatra, Indonesia and other SE Asian countries and in the international well as human health (Pan et al., 2021). MPs are composed of a variety
shipping routes (intentional/accidental release of waste) were trans­ of polymers synthesized from a chain of monomers through polymeri­
ported by ocean currents and dispersed in the east Indian Ocean. Thus, zation reaction, during which unreacted monomers and hazardous ad­
the unique ocean dynamics and monsoon climate in the northern Indian ditives may be present. The sunlight and heat cause weathering of MPs
Ocean influence the distribution and transportation of MPs. in the beach and sea surface, and also releasing of hazardous additives.
As known, rain, flood, and storm events are the key drivers of MP According to a hazard-ranking model based on the United Nations’
transport and contamination in estuarine, coastal and marine environ­ Globally Harmonized System of classification and labelling of chemicals,
ments (Veerasingam et al., 2016a; Hurley et al., 2018; Hitchcock, 2020). the chemical ingredients of >50% of plastics are hazardous (Lithner
Storm surge is another major contributor of transportation of micro­ et al., 2011; Rochman et al., 2013). The ecological risk assessment of
plastics between ocean and land (Lo et al., 2020; Ockelford et al., 2020). MPs in terrestrial and marine sediments is assessed using PHI, PLI and
The frequency and severity of storm surges occur along the ECI is higher PERI parameters. Based on PHI values, the overall risk of MP pollution in
than those on the WCI. In the Bay of Bengal and Arabian Sea, the storm India was categorized as Hazard level IV to V (Table 2). The PHI values
surges generated by the tropical cyclones normally occur during pre-
monsoon (March–May) and post-monsoon (October–November) sea­ Table 2
sons. Therefore, tropical cyclones and associated storm surges not only Terminology used to describe the hazard level criteria for MP pollution.
facilitate the adjustment/migration of shoreline, but also transport MPs
PHI Hazard PLI Hazard PERI Risk
from offshore to the beach. Recently, OceanParcels-v2 has been used in category category category
Lagrangian particle-tracking simulation of plastics released in the
0–1 I <10 I <150 Minor
northern Indian Ocean (van der Mheen et al., 2020). Duncan et al. 1–10 II – – 150–300 Medium
(2020) used Open-source tracking technology (using GPS cellular net­ 10–100 III 10–20 II 300–600 High
works and satellite technology) to understand the transport and fate of 100–1000 IV 20–30 III 600–1220 Danger
plastics in the Ganges river system >1000 V >30 IV >1200 Extreme
danger

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M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

of MPs (Fig. 5) in territorial and marine sediments exhibits serious MP contaminated. The chemical composition of MPs seems to have a minor
pollution trend. For example, the coastal regions of Tamil Nadu, effect on PLI, because PLI was calculated based on the ratio between
Maharashtra and Kerala have high PHI values (>1000) due to the abundance of measured MPs and the background value. The abundance
presence of MPs with high hazard scores, such as PA and PS with high of MPs in the marine environment is affected by regional human ac­
hazard scores. Though the hazard scores of PP, PET and PE are relatively tivities, including rate of industrialization, population density, economic
lower than the hazard scores of PA and PS, we should not ignore them development activities and sea-based activities (fishing and shipping)
while calculating the risk. Moreover, even if the MP concentration is (Jang et al., 2020; Pan et al., 2021). However, the average PLI value
low, its chemical toxicity should not be ignored. found along the Indian coast (5.58) was relatively lower than those re­
PLI is used to measure the degree of MP contamination (Pan et al., ported in China, especially in Changjiang estuary (18.4) (Xu et al., 2018)
2021). Based on PLI, the MP pollution load at each location was calcu­ and Dongshan Bay (14.2) (Pan et al., 2021).
lated (Fig. 6). The PLI values of sediments from ECI were less than 10, The potential ecological risk index (PERI) values of terrestrial and
which indicate the ‘Hazard level I’. However, PLI values from Mahara­ marine sediments along the Indian coast (Fig. 7) show high ecological
shtra (15.5), Karnataka (11.4), and Vembanad Lake (10.45) along the risk (PERI: 300–600) from combined MP polymers in sediments from
west coast of India showed Hazard level II. According to PLI values, Tuticorin (835.7), Kerala coast (597.5), Tamil Nadu coast (476.2),
terrestrial and marine sediments along the WCI are moderately Vembanad Lake (406.7), Goa (346.9), Maharashtra (332.1) and Karna­
contaminated with MPs, while the sediments along the ECI are less taka (303.2). PERI is determined based on the hazard score and

Fig. 5. Polymer hazard index along the Indian coast.

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M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

Fig. 6. Pollution load index along the Indian coast.

abundance of MP polymers. For example, in Tuticorin, the abundance of Ganges) and metropolitans are not studied properly. Moreover, MPs in
PA and PS are high, and that resulted in the highest PERI. Conversely, coastal sediments along the major parts of the ECI (especially, Andhra
less abundance of PA and PS in other parts of Indian coast caused only Pradesh and Odisha coastal region) have not yet been studied. MPs
minor (PERI<150) to medium (150–300) ecological risk. No noticeable along the Indian coast exhibit high polymer hazard range (IV to V) and
correlation between the abundance of MPs (also, PLI) and PHI was PERI values, indicating high ecological risk, of course with limited data.
observed, yet higher abundance of MPs may cause potential ecological Although information is very limited to draw firm conclusion on the
risk. In this study, the combined use of PHI, PLI and PERI provided the polymer hazards and their ecological risk, this study has given a pilot
preliminary ecological risk assessment caused by MP contamination in quantitative measure on the ecological risk caused by MPs in sediments.
terrestrial and marine sediments along the Indian coast. This prioritizes the importance of studying the complete risk assessment
of MPs contamination to elucidate its potential adverse effects on human
3.5. Limitations and future research perspectives health.
Different sample collection and analytical techniques were used for
The literature search clearly showed that very limited reliable data the extraction, quantification and identification of polymers in sedi­
are available on the occurrence of MPs in terrestrial and marine sedi­ ments along the Indian coast (Fig. S4). In a previous work (Veerasingam
ments along the Indian coast, and different sampling and analytical et al., 2020b), we have highlighted the importance of harmonization
methods were followed. The areas around major rivers (especially, and standardization of sampling and analytical methods of MPs in

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M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

Fig. 7. Potential ecological risk index along the Indian coast.

different environmental compartments in India to compare the spatial either confirmed the polymer types or only a few samples were identi­
and temporal variations around the world. Standardized analytical fied using FTIR/Raman spectroscopy (Veerasingam et al., 2020c).
methods are required to assess the reliable abundance of MPs in sedi­ Therefore, the MP data could have contained both natural and synthetic
ments and their ecological risks in the major rivers, coastal and marine fiber type MPs. In this study, the lowest concentration of MP value
environments. detected in the sediment sample was considered as a background value.
The choice of an appropriate background MP value plays a vital role Background value is a comparative measure to discriminate between
in the understanding of PLI and PERI assessment. PLI was proposed by pristine and anthropogenically influenced concentrations of MPs in a
Tomlinson et al. (1980) to assess the level of heavy metal pollution load given environmental sample. Two kinds of background values can be
in the sediments with respect to the baseline metal levels. Since the used: (i) Local Background (LBG), and (ii) Global Background (GBG).
distribution of metals in sediments is derived from both natural The LBG is the MP accumulation in the most pristine site or the MP value
anthropogenic origins, the average values of Earth’s continental crust in the deeper part of the sediment core (Veerasingam et al., 2021),
(Taylor, 1964) or shale (Turekian and Wedepohl, 1961) have been whereas GBG is an average MP concentration given in the literature
widely used as the reference background levels. However, MPs are around the world. GBG gives information concerning sediment quality
derived from anthropogenic origin alone. Therefore, setting up of to be considered at a global scale and allows comparisons beyond the
reference background value for MP pollution load assessment is a crucial local scale. However, due to rapid industrialization and urbanization,
task. Moreover, most of the MP data provided in the literature have not substantial inputs of human-derived MPs get deposited in the sediments,

9
M. Ranjani et al. Marine Pollution Bulletin 163 (2021) 111969

making it difficult or impossible to assess the level of contamination IRCC-2019-002). This work is part of the joint Indo-Russian (DST-RFBR)
using only GBG. Therefore, LBG is suggested, particularly when the research project (INT/RUS/RFBR/P-339). AB is supported by the state
anthropogenic effect and high levels of pollution are suspected. assignment of Marine Hydrophysical Institute, RAS (theme No. 0827-
Most studies reported that fibers and/or particles <300 μm are the 2018-0004). Open Access funding provided by the Qatar National
types of MPs ingested by terrestrial and marine organisms. However, Library.
majority of laboratory toxicology related studies have examined the
impacts of MP ingestion on organisms by particles of <300 μm (often Appendix A. Supplementary data
<100 μm microbeads) in diameter. Much of the existing data on the
physiological and ecological effects of MPs is based on particle sizes that Supplementary data to this article can be found online at https://doi.
majority of seawater sampling studies are not quantified (Covernton org/10.1016/j.marpolbul.2021.111969.
et al., 2019; Kutralam-Muniasamy et al., 2020). Therefore, accurate
quantification of MPs and their polymer types is important for planning
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